多约束仿猫机器人尺寸综合优化
Dimension synthesis optimization of cat-like robots under multiple constraints
吴炳晖 1魏兆翊 1李敏 1程垠钛1
作者信息
- 1. 上海电力大学 能源与机械工程学院,上海 201306
- 折叠
摘要
[目的]针对仿猫机器人研究中多约束参数优化不足的问题,提出了一种使用灰狼算法对仿猫机器人的关键部件进行尺寸优化的方法,使其在多种约束条件的限制下,获得更高的平稳性和灵活性.[方法]首先,对仿猫机器人模型进行力学分析,综合获取多种约束条件和目标函数;然后,使用灰狼算法优化机器人腿部和腰部的尺寸;最后,采用Matlab和Adams软件对仿猫机器人进行了仿真分析.[结果]结果表明,优化后的机器人平稳性指标改进了31.15%,灵活性指标改进了11.28%,验证了该机器人优化方案的合理性.
Abstract
[Objective]In order to solve the problem of insufficient parameters optimization with multiple constraints in the current research of cat-like robots,a method of dimension optimization using the grey wolf algorithm was proposed.The sizes of the key components of the cat-like robot were optimized in the method,and higher stability and flexibility of the robot were ob-tained under the restriction of many constraints.[Methods]Firstly,the mechanics of the cat-like robot model was analyzed,and the multi-constraints and objective function were acquired comprehensively.Secondly,the grey wolf algorithm was used to opti-mize the size of the leg and waist of the robot.Lastly,the simulation analysis of the cat-like robot was carried out in Matlab and Adams software.[Results]The results show that the stability index is improved by 31.15%,and the flexibility index is improved by 11.28%.It verifies the rationality of the optimization scheme of the robot.
关键词
仿猫机器人/运动稳定性/尺寸综合/多约束条件/灰狼算法Key words
Cat-like robot/Motion stability/Dimension synthesis/Multi-constraint/Grey wolf algorithm引用本文复制引用
出版年
2025
NETL
NSTL
万方数据